Doctoral Researcher “DNN-based multi-modal speech enhancement for hearing devices”

About us

The School VI of Medicine and Health Sciences comprises the fields of human medicine, medical physics and acoustics, neurosciences, psychology and health services research. Together with the four regional hospitals, School VI forms the University Medicine Oldenburg. Furthermore, the university cooperates closely with the University Medicine of the University of Groningen.

The doctoral research position is embedded within the Signal Processing Division (http://www.sigproc.uni-oldenburg.de) and the Collaborative Research Centre Hearing Acoustics (https://uol.de/en/sfb-1330-hearing-acoustics). The main activities of the Signal Processing Division center around signal processing for acoustical and biomedical applications, with a focus on hearing aids and speech communication devices. More specifically, research topics in the areas of microphone array processing, speech enhancement and acoustic scene analysis are addressed, using a combination of model-based statistical signal processing techniques and data-driven machine learning methods. The Signal Processing Division has access to excellent high-performance computing facilities, measurement equipment and labs, e.g., a unique lab with variable acoustics (see demos on YouTube channel: https://www.youtube.com/@signalprocessingunioldenbu1018)  

Your tasks

• conduct research on speech enhancement algorithms for hearing devices in dynamic acoustic environments with multiple talkers, including algorithm design, implementation, and experimental validation. A central element is the use of multi-modal sensor data, e.g., electrooculography (EOG) and head orientation (accelerometer) in combination with the microphone signals from the hearing devices. Algorithm design will involve a combination of signal processing and machine learning methods.
• conduct research on own-voice detection and processing in the context of multi-modal speech enhancement algorithms for hearing devices
• close collaboration with cooperation partners of the project
• publish research results in scientific journals
• active participation in international conferences
• active participation in research meetings and seminars of the Collaborative Research Centre Hearing Acoustics and the Department of Medical Physics and Acoustics
• supervise students and contribute to teaching in tutorials 

Your profile

Required qualifications

• academic university degree (Master or equivalent) in electrical engineering, biomedical engineering, computer science, engineering physics, hearing technology, or a related discipline
• excellent grades in digital signal processing and machine learning courses
• knowledge and scientific experience in at least two of the following research fields: speech/audio signal processing, biomedical signal processing, machine learning
• excellent programming skills (e.g., python, Matlab)
• excellent written and spoken English language skills

Preferred qualifications:

• experience with DNN-based speech enhancement algorithms
• experience with signal processing algorithms for hearing devices
• experience with multi-modal signal processing algorithms
• good communication skills
• ability to work in a team

We offer

• Integration into a dedicated team and an excellent scientific environment
• Intensive support during your doctorate
• Access to excellent acoustical labs and computing facilities
• Payment in accordance with collective bargaining law (special annual payment, company pension scheme, asset-related benefits) incl. 30 days annual leave
• Support and guidance during your onboarding phase
• A family-friendly environment with flexible working hours (flexitime) and the possibility of pro-rata mobile work
• An extensive and free further education programme as well as programmes geared toward the promotion of early-career researchers (https://uol.de/en/school6/early-career)

Our standards

The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification.

Further information

The position serves for personal scientific qualification (doctorate).

Contact

For further information, please contact Prof. Dr. Simon Doclo (simon.doclo@uni-oldenburg.de; http://www.sigproc.uni-oldenburg.de).